642 citations · 951 across the 7 of their papers we have counts for
5 papers · 1 filter
A Probabilistic Model for Discriminative and Neuro-Symbolic Semi-Supervised Learning
Carl Allen, Ivana Balažević, Timothy Hospedales
Much progress has been made in semi-supervised learning (SSL) by combining methods that exploit different aspects of the data distribution, e.g. consistency regularisation relies o…
Multi-scale Attributed Node Embedding
Benedek Rozemberczki, Carl Allen, Rik Sarkar
We present network embedding algorithms that capture information about a node from the local distribution over node attributes around it, as observed over random walks following an…
Interpreting Knowledge Graph Relation Representation from Word Embeddings
Carl Allen, Ivana Balažević, Timothy Hospedales
Many models learn representations of knowledge graph data by exploiting its low-rank latent structure, encoding known relations between entities and enabling unknown facts to be in…
TuckER: Tensor Factorization for Knowledge Graph Completion
Ivana Balažević, Carl Allen, Timothy M. Hospedales
Knowledge graphs are structured representations of real world facts. However, they typically contain only a small subset of all possible facts. Link prediction is a task of inferri…
Hypernetwork Knowledge Graph Embeddings
Ivana Balažević, Carl Allen, Timothy M. Hospedales
Knowledge graphs are graphical representations of large databases of facts, which typically suffer from incompleteness. Inferring missing relations (links) between entities (nodes)…